1. Field of the Invention
The present invention involves the field of ultrasound imagery. More particularly, the present invention involves spatial calibration of ultrasound probes for intra-operative use.
2. Discussion of the Related Art
Computer Integrated Surgery has revolutionized surgical procedures, whereby 3D imagery of a target volume is created to enable a surgeon to more precisely and accurately position surgical tools within a patient. To serve this purpose, the imaging system, or guidance modality, should provide 3D imagery in real time; it must not be excessively obstructive or burdensome in an operating environment; and it must provide 3D imagery with sufficient accuracy and precision to provide effective surgical planning and execution.
Ultrasound has become a popular guidance modality for medical procedures, due to its real-time operation, safety, low cost, and convenience of use in an operating room environment. Although it is not a “true 3D” imaging modality, such as Magnetic Resonance Imaging (MRI) and Computer Tomography (CT), techniques have been developed to convert multiple ultrasound 2D images into a 3D image in order to provide image guidance for surgeons while exploiting the benefits and conveniences of ultrasound.
Components of a conventional ultrasound system 100 are illustrated in FIG. 1. The ultrasound system 100 includes a transmitter 105 having a transmitter reference frame 130; and an ultrasound probe 110 having a probe reference frame 135. The ultrasound probe 110 transmits and receives energy in a scan plane 142, and projects a plurality of pixels 140 in a pixel reference frame 145. A conventional ultrasound system 100 may also include tracking sensors 125 to monitor the position and orientation of the ultrasound probe 110. The ultrasound system 100 is used to collect multiple 2D ultrasound images, which are assembled into a 3D image space 155 having a construction reference frame 150 (hereinafter “construction frame”).
In order to provide image guidance during a surgical procedure, 2D ultrasound images acquired by the ultrasound system 100 must be registered or mapped in real-time into a 3D image space 155, which encompasses a target volume within the patient undergoing surgery. Although there are ultrasound probes that acquire 3D images, these probes need to be spatially calibrated as well. Registering pixels from pixel reference frame 145 to the 3D image space 155 requires a transformation matrix encompassing a series of constituent coordinate transformation matrices: e.g., from the pixel frame 145 to the ultrasound probe reference frame 135; from the ultrasound probe frame 135 to the transmitter reference frame 130; and from the transmitter reference frame 130 to the construction frame 150. Of these transformation matrices, the most difficult to determine is the transformation matrix from the pixel reference frame 145 to the ultrasound probe reference frame 135 (hereinafter the “probe calibration matrix”).
According to the related art, spatial calibration is the act of determining each of the aforementioned transformation matrices, which is typically done before a medical procedure. In related art spatial calibration, the ultrasound probe 110 is placed and oriented such that it acquires an image of a calibration target, or phantom, which has well defined spatial features. Using image processing techniques such as segmentation, the well defined features of the phantom are identified and located in the acquired ultrasound image, and the position and orientation of the phantom is derived from the segmented image. In the related art approach, images are acquired with the ultrasound probe 110 placed in a single position and orientation. If the position and location of the phantom are known relative to the construction frame 155, the probe calibration matrix can be derived. By comparing the locations of the identified imaged features of the phantom with known locations and relative orientations of these features, the orientation of the phantom may be determined relative to the orientation of the ultrasound probe, and the probe calibration matrix may be derived by correlating the segmented images of the phantom with the phantom's known spatial characteristics.
Image processing techniques such as segmentation are computationally intensive and may not be feasible to compute in real time, based on the number of images acquired. Typical segmentation is performed on several hundred images. The large number of images not only requires time to process, but it increases the likelihood of errors that may render the probe calibration matrix invalid.
According to the related art, once the transformation matrices, including the probe calibration matrix, are known, a pixel 140 may be registered into the 3D image space 155 defines by the construction frame 150. The transformation of a pixel 140 location from the pixel reference frame 145 to the construction frame 155 can be expressed as:Cx=CTTTTRRTPPx,where Px is the location of pixel 140 in pixel reference frame 145; Cx is the location of pixel 140 in construction frame 155; RTP is the coordinate transformation matrix from the pixel reference frame 145 to the ultrasound probe reference frame 135 (i.e., the probe calibration matrix); TTR is the coordinate transformation from the ultrasound probe reference frame 135 to the transmitter reference frame 130, which may be measured using tracking sensors 125; and CTT is the coordinate transformation from the transmitter reference frame 130 to the construction frame 155, which may be measured.
The accuracy and precision of registering ultrasound image pixels 140 into the construction frame 155 is limited by the accuracy and precision of each of the above transformation matrices. The weakest link in this chain is the accuracy and precision of the probe calibration matrix RTP. Accordingly, a primary challenge in spatial calibration is in determining the probe calibration matrix RTP.
There are errors intrinsic to the conventional spatial calibration process that limit its precision and accuracy, including the following: imprecision in fabrication of the phantom, subsequent mechanical distortions of the phantom, lack of precision in characterizing the features of the phantom, spatial co-registration or ambiguities, and limits to numerical solution optimizations. As such, the quality of the calibration is limited to the accuracy and precision to which the phantom is characterized.
An additional disadvantage of the related art spatial calibration is that since it cannot be performed intra-operatively, partly because it cannot be performed in real time, it is vulnerable to subsequent changes that may render any or all of the calibration matrices invalid without warning. Such post-calibration changes may be brought on by mechanical alteration to the tracking sensors and changes in tissue temperature. The effect of post-calibration changes may include inaccurate 3D image, resulting in incorrect surgical instrument placement.
Although the above discussion involves ultrasound, the same issues may be encountered for any imaging system for which 2D images are assembled into a 3D image space. Or more generally, the same issues may arise in which a 2D imaging system is spatially calibrated in order to register image products into another reference frame.